6 citations · 9 across the 6 of their papers we have counts for
6 papers
Combining Neural Networks and Symbolic Regression for Analytical Lyapunov Function Discovery
Jie Feng, Haohan Zou, Yuanyuan Shi
We propose CoNSAL (Combining Neural networks and Symbolic regression for Analytical Lyapunov function) to construct analytical Lyapunov functions for nonlinear dynamic systems. Thi…
Stability-Constrained Learning for Frequency Regulation in Power Grids with Variable Inertia
Jie Feng, Manasa Muralidharan, Rodrigo Henriquez-Auba +2
The increasing penetration of converter-based renewable generation has resulted in faster frequency dynamics, and low and variable inertia. As a result, there is a need for frequen…
Ventilation and Temperature Control for Energy-efficient and Healthy Buildings: A Differentiable PDE Approach
Yuexin Bian, Xiaohan Fu, Rajesh K. Gupta +1
In this paper, we introduce a novel framework for building learning and control, focusing on ventilation and thermal management to enhance energy efficiency. We validate the perfor…
Leveraging Predictions in Power System Frequency Control: an Adaptive Approach
Wenqi Cui, Guanya Shi, Yuanyuan Shi +1
Ensuring the frequency stability of electric grids with increasing renewable resources is a key problem in power system operations. In recent years, a number of advanced controller…
Robust Online Voltage Control with an Unknown Grid Topology
Christopher Yeh, Jing Yu, Yuanyuan Shi +1
Voltage control generally requires accurate information about the grid's topology in order to guarantee network stability. However, accurate topology identification is a challengin…
CEM-GD: Cross-Entropy Method with Gradient Descent Planner for Model-Based Reinforcement Learning
Kevin Huang, Sahin Lale, Ugo Rosolia +2
Current state-of-the-art model-based reinforcement learning algorithms use trajectory sampling methods, such as the Cross-Entropy Method (CEM), for planning in continuous control s…